数据为中心的AI应用于多学科领域

English | 2024 | ISBN: 9781003461500 | 309 pages | True PDF | 19.37 MB

This book explores the need for a data‑centric AI approach and its application in the multidisciplinary domain, compared to a model‑centric approach. It examines the methodologies for data‑centric approaches, the use of data‑centric approaches in different domains, the need for edge AI and how it differs from cloud‑based AI. It discusses the new category of AI technology, "data‑centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, data‑centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods.

• Includes a collection of case studies with experimentation results to adhere to the practical approaches

• Examines challenges in dataset generation, synthetic datasets, analysis, and prediction algorithms in stochastic ways

• Discusses methodologies to achieve accurate results by improving the quality of data

• Comprises cases in healthcare and agriculture with implementation and impact of quality data in building AI applications

这本书探讨了数据为中心的AI方法的需求及其在多学科领域的应用，与模型为中心的方法进行比较。它研究了数据为中心的方法的 methodologies，在不同领域中的使用情况，边缘AI的必要性以及其与基于云的AI的不同之处。讨论了一种新的AI技术类别：“数据为中心的AI”（DCAI），该技术专注于从数据中理解、利用和得出结论。通过添加机器学习和大数据分析工具，数据为中心的AI修改了这一方法，使其能够从数据中学习而不是依赖算法。因此，它可以做出更明智的选择并提供更精确的结果。此外，与传统AI方法相比，它有潜力显著更具可扩展性。 - 包含一系列案例研究，以实验结果为依据，符合实际应用的方法。 - 探讨了在随机方式下生成数据集、合成数据集、数据分析和预测算法方面面临挑战的问题。 - 讨论提高数据质量的方法来实现准确的结果。 - 介绍医疗保健和农业领域中高质量数据的应用实例及其对构建AI应用程序的影响。

---

Download from free file storage

 Download from rapidgator.net  Download from nitroflare.com

---

我要反馈

---

本站不对文件进行储存，仅提供文件链接，请自行下载，本站不对文件内容负责，请自行判断文件是否安全，如发现文件有侵权行为，请联系管理员删除。